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Activity Number: 514
Type: Topic Contributed
Date/Time: Wednesday, August 7, 2013 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Consulting
Abstract - #310412
Title: Statistics Meets Systems
Author(s): Ralf Herbrich*+
Companies: Amazon
Keywords:
Abstract:

Over the past few years, we have entered the world of big and structured data- a trend largely driven by the exponential growth of Internet-based online services such as Search, eCommerce and Social Networking as well as the ubiquity of smart devices with sensors in everyday life. This poses new challenges for statistical inference and decision-making as some of the basic assumptions are shifting: *the ability to optimize both the likelihood and loss functions *the ability to store the parameters of (data) models *the level of granularity and 'building blocks' in the data modeling phase *the importance of priors vs. likelihoods *the interplay of computation, storage, communication and inference and dexision-making techniques In this talk, I will discuss the implications of big and structured data for Statistics and the convergence of statistical model and distributed systems. I will present one of the most versatile modeling techniques that combines systems and statistical properties -factor graphs- and review a series of approximate inference techniques such as distributed message passing and Gibbs sampling. The talk will be concluded with an overview of real-world problems at Amazon.


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